Python Job: Analyst - GeoAnalytics

WHAT YOU'LL DO

GAMMA is BCG’s premier data science and advanced analytics capability with 1000+ data scientists, engineers, and analysts globally. Within GAMMA, the Specialty team (GAMMA S) is a hybrid client-facing/consulting-support that leverages available tools and code bases to deliver powerful and specialized insights that help our clients tackle their most pressing business problems. We partner with BCG case teams and practices across the full analytics value chain: framing new business challenges and problems, designing and executing innovative analytical solutions, and interpreting findings for our clients. GeoAnalytics is a sub-team in GAMMA S with expertise in geospatial analytics and tools. Our 30+ member team is a global resource, working with clients in every BCG region and in every industry area. It is a core member of a rapidly growing analytics enterprise at BCG – a constellation of teams focused on driving practical results for BCG clients by applying leading edge technologies.

YOU'RE GOOD AT

As an Analyst in GeoAnalytics, you will be solving a variety of location-based analytical problems for our clients. You will utilize your knowledge of geospatial data and analytics while using a variety of tools such as Geographic Information Systems (GIS), Python, and visualization/analytical platforms (ex. Tableau, Alteryx). You will leverage a range of techniques such as geospatial clustering, network analysis, location-based optimization and predictive analytics/modeling.

YOU BRING (EXPERIENCE & QUALIFICATIONS)

Education & Experience:

• 1-3 years of relevant work experience in GeoAnalytics with advanced degree preferred
• Relevant degree in geospatial related field such as: Geography, Remote Sensing, Urban Planning, Statistics/GeoStatistics, Applied Mathematics, or Computer Science
• Previous experience working in a global organization or professional services firm is preferred
• Data management skills (e.g. data modeling, data integrity QA/QC, database administration)
• GIS software such as ESRI ArcGIS, QGIS, CARTO
• Data science programming/coding in Python and/or R
• Descriptive statistics and statistical methods (e.g. correlation, regression, clustering, etc.) with applications in machine learning
• Exposure to BI/Data visualization platforms such as Tableau, Power BI, etc.
• Handling, processing, and deriving insights from remotely sensed data preferred